R: Calculate Community Connectedness or Modularity

getCommunityConnectedness {linkcomm} | R Documentation

## Calculate Community Connectedness or Modularity

### Description

This function returns a measure of how relatively outwardly or inwardly connected a community is.

### Usage

    getCommunityConnectedness(x, clusterids = 1:x$numbers[3], conn = "conn",
                              normalise = TRUE, verbose = FALSE)

### Arguments

`x` | An object of class `linkcomm`.
`clusterids` | An integer vector of community IDs. Defaults to all communities.
`conn` | A character string naming the connectedness measure to use. Can be one of `"conn"` or `"mod"` (see Details below). Defaults to `"conn"`.
`normalise` | Logical, whether to normalise community connectedness measures by the number of nodes in individual communities. Defaults to TRUE.
`verbose` | Logical, whether to display the progress of the calculation on the screen. Defaults to FALSE.

### Details

The connectedness and modularity of different communities indicates whether a particular community is bridging several other communities, or existing as a relatively isolated module. The modularity of community i is

M(i) = (e_{w}(i)/n_{i}(n_{i}-1)/2).(e_{b}(i)/n_{i}*d)^-1

where e_{w}(i) is the number of edges within community i, e_{b}(i) is the number of edges community i makes to other communities, n_{i} is the number of nodes in community i, and \hat{d} is the average degree in the network. Community connectedness is the inverse of this value.

### Value

A named numerical vector, where the names are community IDs and the numbers are community connectedness or modularity scores.

### Author(s)

Alex T. Kalinka alex.t.kalinka@gmail.com

### References

Kalinka, A.T. and Tomancak, P. (2011). linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type. Bioinformatics 27, 2011-2012.

### See Also

`getCommunityCentrality`

### Examples

    ## Generate graph and extract link communities.
    g <- swiss[,3:4]
    lc <- getLinkCommunities(g)

    ## Get community connectedness.
    cc <- getCommunityConnectedness(lc, normalise = FALSE)

[Package linkcomm version 1.0-14 Index]